At a Glance
- Tasks: Tackle complex software challenges in automated trading and develop innovative solutions.
- Company: Leading algorithmic trading firm in London with a focus on cutting-edge technology.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Join a dynamic team solving real-world problems at the intersection of finance and technology.
- Qualifications: Experience in software engineering and a strong mathematical background.
The predicted salary is between 70000 - 90000 £ per year.
When you think about being challenged by a set of interesting problems in software engineering, what do those typically look like? We're working with a team of engineers at an algorithmic trading firm in London, which solves problems that sit at an incredibly interesting intersection: financial instruments, game theory and distributed systems.
Why is their work interesting?
- Latency. They write code where the execution path is profiled in microseconds because they're racing other teams to the same opportunity.
- Profit discovery. Finding an edge in automated trading means they've built their own data infrastructure. This indexes on-chain state, reconstructs order books from venues, tracks wallet behaviour across chains. Their pipelines process millions of events and make them queryable in milliseconds.
- Probabilistic trading models. When they submit a trade, they don't know if it lands, when it lands, or what state the world is in when it does. The code's logic has to reason about: what if this reverts? What if gas spikes and I'm outbid? What if the price moves between simulation and inclusion? The code they write simulates the full execution against a forked state before committing.
- Heavily math oriented. Their work solves for optimal trade size across venues with non-linear price impact, factoring execution costs at execution time. This may look like implementing constant product formula, concentrated liquidity tick math and Curve stableswap invariants directly in their simulation layer so they can price routes without hitting an RPC.
- Signal to noise analysis. Where they trade, the data is public and permanent, which sounds great until you realise everyone has the same data. Their edge is in how fast it's processed, reconstructed and opportunities identified before they get arbed away. This means they end up writing a lot of heuristics for classifying transactions.
Who they need to join them? There are two avenues they are prioritising:
- Software Engineer with several years of experience from a tech-driven company, supported by top-class academics. Existing team members hold IMO/IOI medals.
- Software Engineer from the world of proprietary trading, who may have experimented with on-chain trading strategies before.
Senior Software Engineer employer: QNT Partners
Join a leading algorithmic trading firm in London, where you'll be immersed in a dynamic work culture that thrives on innovation and collaboration. With a focus on cutting-edge technology and complex problem-solving, we offer exceptional growth opportunities for our engineers, alongside competitive benefits and a stimulating environment that encourages continuous learning and development. Experience the thrill of working at the forefront of financial technology, where your contributions directly impact our success in the fast-paced world of automated trading.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Software Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, conferences, or even online webinars related to automated trading and software engineering. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects, especially those that involve financial instruments or distributed systems. Share it on platforms like GitHub and make sure to link it in your applications. We love seeing what you can do!
✨Tip Number 3
Prepare for technical interviews by brushing up on your algorithms and data structures. Practice coding challenges that focus on latency-sensitive applications. Remember, they want to see how you think under pressure, so simulate real interview conditions!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates who are ready to tackle interesting problems in software engineering.
We think you need these skills to ace Senior Software Engineer
Some tips for your application 🫡
Show Your Passion for Problem-Solving:When you’re writing your application, let us see your enthusiasm for tackling complex problems. Share examples of how you've approached challenging software engineering tasks, especially those that involve financial instruments or distributed systems.
Highlight Relevant Experience:Make sure to emphasise your experience in tech-driven environments or proprietary trading. We want to know about the projects you've worked on that relate to automated trading, data infrastructure, or probabilistic models. Tailor your CV to reflect this!
Be Clear and Concise:We appreciate clarity! When you're crafting your application, keep it straightforward and to the point. Use bullet points where possible to make your achievements stand out, and avoid jargon unless it's relevant to the role.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen to join our team at StudySmarter!
How to prepare for a job interview at QNT Partners
✨Know Your Algorithms
Brush up on your algorithms and data structures, especially those relevant to trading systems. Be prepared to discuss how you would optimise code for latency and efficiency, as this is crucial in automated trading.
✨Understand the Financial Landscape
Familiarise yourself with financial instruments and trading strategies. Being able to speak knowledgeably about market dynamics and how they relate to your coding decisions will impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to tackle hypothetical scenarios that involve probabilistic trading models. Think through how you would handle unexpected situations in trading, such as price fluctuations or gas spikes, and articulate your thought process clearly.
✨Demonstrate Your Mathematical Acumen
Since the role is heavily math-oriented, be ready to discuss mathematical concepts relevant to trading, like non-linear price impact and execution costs. Show how you can apply these concepts in practical coding scenarios.
